参考资料#
Arthur Allshire, Mayank MittaI, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, and Animesh Garg. Transferring dexterous manipulation from gpu simulation to a remote real-world trifinger. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 11802–11809. IEEE, 2022.
Samuel Buss. Introduction to inverse kinematics with jacobian transpose, pseudoinverse and damped least squares methods. IEEE Transactions in Robotics and Automation, 17:, 2004.
Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, and Nathan Ratliff. Rmpflow: a geometric framework for generation of multitask motion policies. IEEE Transactions on Automation Science and Engineering, 18(3):968–987, 2021. doi:10.1109/TASE.2021.3053422.
Ankur Handa, Arthur Allshire, Viktor Makoviychuk, Aleksei Petrenko, Ritvik Singh, Jingzhou Liu, Denys Makoviichuk, Karl Van Wyk, Alexander Zhurkevich, Balakumar Sundaralingam, and others. Dextreme: transfer of agile in-hand manipulation from simulation to reality. arXiv preprint arXiv:2210.13702, 2022.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition, 770–778. 2016.
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter. Learning agile and dynamic motor skills for legged robots. Science Robotics, 4(26):eaau5872, 2019.
O. Khatib. A unified approach for motion and force control of robot manipulators: the operational space formulation. IEEE Journal on Robotics and Automation, 3(1):43–53, 1987. doi:10.1109/JRA.1987.1087068.
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, and others. Isaac gym: high performance gpu-based physics simulation for robot learning. arXiv preprint arXiv:2108.10470, 2021.
Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, and Animesh Garg. Articulated object interaction in unknown scenes with whole-body mobile manipulation. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.
Mayank Mittal, Calvin Yu, Qinxi Yu, Jingzhou Liu, Nikita Rudin, David Hoeller, Jia Lin Yuan, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, and Animesh Garg. Orbit: a unified simulation framework for interactive robot learning environments. IEEE Robotics and Automation Letters, 8(6):3740–3747, 2023. doi:10.1109/LRA.2023.3270034.
Yashraj Narang, Kier Storey, Iretiayo Akinola, Miles Macklin, Philipp Reist, Lukasz Wawrzyniak, Yunrong Guo, Adam Moravanszky, Gavriel State, Michelle Lu, and others. Factory: fast contact for robotic assembly. arXiv preprint arXiv:2205.03532, 2022.
Nikita Rudin, David Hoeller, Marko Bjelonic, and Marco Hutter. Advanced skills by learning locomotion and local navigation end-to-end. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), volume, 2497–2503. 2022. doi:10.1109/IROS47612.2022.9981198.
Nikita Rudin, David Hoeller, Philipp Reist, and Marco Hutter. Learning to walk in minutes using massively parallel deep reinforcement learning. In Conference on Robot Learning, 91–100. PMLR, 2022.
Jinghuan Shang, Karl Schmeckpeper, Brandon B May, Maria Vittoria Minniti, Tarik Kelestemur, David Watkins, and Laura Herlant. Theia: distilling diverse vision foundation models for robot learning. arXiv preprint arXiv:2407.20179, 2024.
Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, and Giuseppe Oriolo. Force control. Springer, 2009.